1. Field of Invention
This invention relates to systems and methods for controlling devices and processes.
2. Description of Related Art
Market-based controllers and adaptive multi-agent control systems are known. These controllers and systems include those disclosed in U.S. Pat. No. 6,119,052, which discloses a market-based controller for controlling the motion of an object on a transport assembly. The transport assembly is formed using sensors and actuators located close to each other. A control system controls motion of the object on the transport by allocating quantities of system resources to selected actuator units. The control system includes market agents, an actuator distributor and a market auctioneer. The market agents submit bids to purchase quantities of the system resource for selected ones of the actuator units. The actuator distributor specifies available quantities of the system resource for consumption by the actuator units.
The market auctioneer, which is coupled to the market agents and the actuator distributor, receives the bids submitted by the market agents and the available quantities of the system resource specified by the actuator distributor to allocate the system resource that satisfies an aggregation of the bids. To efficiently allocate a fixed amount of a system resource, such as air pressure, directed to the actuators, the market controller maps each market agent to points in space in the transport assembly, as well as points in time relative to a system clock. Using information gathered from the sensor sites, each market agent determines whether to bid on the fixed amount of the relevant system resource at each bid interval. Using the bids submitted by the market agents, a market equilibrium price and quantity are computed by a market auctioneer. The system resource, such as air pressure, purchased by each market agent is then distributed to the actuators mapped to each market agent.
U.S. Pat. No. 6,027,112 discloses an adaptive multi-agent control system for controlling object motion with smart matter. The multi-agent control system disclosed in the '112 patent includes a learning mechanism that takes advantage of the proximate coupling between sensors and actuators. The learning mechanism improves system performance by making iterative changes to an interaction matrix that represents the organizational structure of the multi-agent control system.